This study analyzes the forest flammability hazard in the south of Tyumen Oblast (Western Siberia, Russia) and identifies variation patterns in fire areas depending on weather and climate characteristics in 2008-2023. Using correlation analysis, we proved that the area of forest fires is primarily affected by maximum temperature, relative air humidity, and the amount of precipitation, as well as by global climate change associated with an increase in carbon dioxide in the atmosphere and the maximum height of snow cover. As a rule, a year before the period of severe forest fires in the south of Tyumen Oblast, the height of snow cover is insignificant, which leads to insufficient soil moisture in the following spring, less or no time for the vegetation to enter the vegetative phase, and the forest leaf floor remaining dry and easily flammable, which contributes to an increase in the fire area. According to the estimates of the CMIP6 project climate models under the SSP2-4.5 scenario, by the end of the 21st century, a gradual increase in the number of summer temperatures above 35 degrees C is expected, whereas the extreme SSP5-8.5 scenario forecasts the tripling in the number of such hot days. The forecast shows an increase of fire hazardous conditions in the south of Tyumen Oblast by the late 21st century, which should be taken into account in the territory's economic development.

The Qinghai-Tibetan Plateau (Q-TP hereafter) has experienced dramatic warming in recent decades, resulting in severe effects on the ecosystems and downstream. However, none of previous studies investigated elevationdependency temperature trend with the high resolution over the long-term period. Based on monthly temperature dataset with 0.1 developed by generative adversarial network, elevation-dependency temperature trend over the Q-TP and 5 climate zones (humid, humid-semihumid, semihumid, semiarid, arid region) during 1901-1946, 1946-1965, 1965-1997 and 1997-2015 are investigated. Snow cover (SNC), high cloud cover (HCC), middle cloud cover (MCC), specific humidity (SHUM) and soil moisture content (SOILM) are introduced to analyze possible mechanism. There are 4 cases of elevation-dependency temperature trend, which are positive/negative elevation-dependency warming (EDW+/EDW-) and cooling (EDC+/EDC-). These patterns (EDW+, EDW-, EDC+ and EDC-) are identified as warming/cooling trends that become stronger/weaker with increasing elevation. EDW- signal is found during 1901-1946 due to the influence of SOILM. The most prominent EDW- signal occurs over the arid region. EDC+/- is presented during 1946-1965 under the dominance of SHUM and SOILM. The stronger EDC signal is shown over the arid and semiarid region than over the humidsemihumid region. The subtle EDW+ signal is shown over the semihumid, semiarid and arid regions during 1965-1997 when SOILM has a relatively large contribution to temperature trend. The robust EDW+ signal is exhibited from 1997 to 2015 when SNC plays a vital role in regulating the temperature change. There is a more significant EDW+ over the humid, humid-semihumid, and semihumid regions than that over the semiarid and arid regions during this period. Above all, SNC, SHUM and SOILM are found to be the primary contributors to elevation-dependency temperature trend. SOILM and SHUM are associated with hydrological effects and control temperature variations over the Q-TP during 1901-1997. SNC is related to snow/ice-albedo feedback and dominates temperature variations over the Q-TP during 1997-2015.

The understanding of temperature trends in high elevation mountain areas is an integral part of climate change research and it is critical for assessing the impacts of climate change on water resources including glacier melt, degradation of soils, and active layer thickness. In this study, climate changes were analyzed based on trends in air temperature variables (T-max, T-min, T-mean), and Diurnal Temperature Range (DTR) as well as elevation-dependent warming at annual and seasonal scales in the Headwaters of Yangtze River (HWYZ), Qinghai Tibetan Plateau. The Base Period (1965-2014) was split into two subperiods; Period-I (1965-1989) and Period-II (1990- 2014) and the analysis was constrained over two subbasins; Zhimenda and Tuotuohe. Increasing trends were found in absolute changes in temperature variables during Period-II as compared to Period-I. T-max, T-min, and T-mean had significant increasing trends for both sub-basins. The highest significant trends in annual time scale were observed in T-min (1.15 degrees C decade(-1)) in Tuotuohe and 0.98 degrees C decade(-1) in Zhimenda sub-basins. In Period-II, only the winter season had the highest magnitudes of T-max and T-min 0.58 degrees C decade(-1) and 1.26 degrees C decade(-1) in Tuotuohe subbasin, respectively. Elevation dependent warming analysis revealed that T-max, T-min and T-mean trend magnitudes increase with the increase of elevations in the middle reaches (4000 m to 4400 m) of the HWYZ during Period-II annually. The increasing trend magnitude during Period-II, for T-max, is 1.77, 0.92, and 1.31 degrees C decade(-1), for T-min 1.20, 1.32 and 1.59 degrees C decade(-1), for T-mean 1.51, 1.10 and 1.51 degrees C decade(-1) at elevations of 4066 m, 4175 m and 4415 m respectively in the winter season. T-mean increases during the spring season for > 3681 m elevations during Period-II, with no particular relation with elevation dependency for other variables. During the summer season in Period- II, T-max, T-min, T-mean increases with the increase of elevations (3681 m to 4415 m) in the middle reaches of HWYZ. Elevation dependent warming (EDW), the study concluded that magnitudes of T-min are increasing significantly after the 1990s as compared to T-max in the HWYZ. It is concluded that the climate of the HWYZ is getting warmer in both sub-basins and the rate of warming was more evident after the 1990s. The outcomes of the study provide an essential insight into climate change in the region and would be a primary index to select and design research scenarios to explore the impacts of climate change on water resources.